Simulation and analysis of an improved LEACH algorithm in wireless sensor network

Abstract. Increasing the lifespan of a group of distributed wireless sensors is one of the major challenges in research. This is especially important for distributed wireless sensor nodes used in harsh environments since it is not feasible to replace or recharge their batteries. Thus, the popular low-energy adaptive clustering hierarchy (LEACH) algorithm uses the “computation and communication energy model” to increase the lifespan of distributed wireless sensor nodes. As an improved method, we present here that a combination of three clustering algorithms performs better than the LEACH algorithm. The clustering algorithms included in the combination are the k-means+ + , k-means, and gap statistics algorithms. These three algorithms are used selectively in the following manner: the k-means+ + algorithm initializes the center for the k-means algorithm, the k-means algorithm computes the optimal center of the clusters, and the gap statistics algorithm selects the optimal number of clusters in a distributed wireless sensor network. Our simulation shows that the approach of using a combination of clustering algorithms increases the lifespan of the wireless sensor nodes by 15 % compared with the LEACH algorithm. This paper reports the details of the clustering algorithms selected for use in the combination approach and, based on the simulation results, compares the performance of the combination approach with that of the LEACH algorithm.

Wireless sensor networks (WSN) are a yield of advancement in information technology and the requirement of large-scale communication infrastructures. Routing of data via selected paths is a critical task in WSN as process need to be carried on under resource constraint situations. This route identification problem can be better handled by employing appropriate heuristic bio-inspired computational intelligence optimization method. The most frequently applied routing is hierarchical routing algorithm is Low Energy Adaptive Clustering Hierarchy (LEACH) algorithm which has limitations in identifying energy efficient inter and intra route communication, identification of number of cluster head (CH), an eminent node to communicate to CH and Base Station (BS), selection of CH, and computing residual energy level, etc. Hence, researchers are focusing on boosting the capability of LEACH clustering algorithm by applying heuristic bio-inspired computational intelligence optimization methods. The proposed work is an attempt in this direction through applying heuristic bio-inspired Grey Wolf Optimization algorithm (GWO) for improving the performance of LEACH algorithm. In this paper, focus is given to increase the overall network time by adapting two modifications to conventional algorithms (i) selection of vice cluster head (VCH) in addition to CH (VCH node will replace the CH when CH when CH node goes down due to unexpected reasons as sensor node work under critical and uninterruptable environments and (ii) selection of intra and inter relay nodes (intra relay node will enhance the life span during CH data gathering and inter relay node will further enhance the life span of CH by acting as a mediator between CH an BS). The Spyder-py3 tool is used to simulate the proposed algorithms, LEACH Binary Grey Wolf search based Optimization (LEACH-BGWO) and LEACH Discrete Grey Wolf search based Optimization (LEACH-DGWO) protocols. The proposed work is compared with cluster based LEACH algorithm, chain based power-efficient gathering in sensor information systems (PEGASIS) algorithm, bio-inspired GWO and Genetic Algorithm data Aggregation (GADA) LEACH protocols. The results prove that both proposed algorithms outperformed other conventional algorithms in terms of prolonged network lifespan and increased throughput. Among proposed algorithms LEACH-BGWO outperformed LEACH-DGWO

Due to the limitation of power and memory size for WSN (wireless sensor networks), the routing protocol of wireless sensor networks must maintain small routing information and reduce the power consumption as much as possible. LEACH (low-energy adaptive clustering hierarchy) protocol and PEGASIS (power-efficient gathering in sensor information systems) protocol are analyzed firstly in this paper. Use for reference of the ideas used in both of the two protocols of reducing power dissipation, a three-layered routing protocol for WSN based on LEACH (TL-LEACH) is given. Then, this improved LEACH protocol is simulated and the simulation results show that TL-LEACH protocol is with greatly improved WSN lifetime than LEACH protocol.

Wireless sensor networks (WSNs) have been considered as a promising method for reliably monitoring both civil and military environments under hazardous or dangerous conditions. Due to such environments, the power supplies for sensors in the network are not usually rechargeable or replaceable. Therefore, the energy efficiency is critical for the lifetime and cost of WSN. Numerous mechanisms have been proposed to reduce the impact of communication protocols on the overall energy dissipation of WSN. The low-energy adaptive clustering hierarchy (LEACH) and another improved centralized LEACH deploy randomized rotation of cluster-heads to evenly distribute the energy load among all sensors in a WSN. This paper proposes an improved LEACH (LEACH-C) algorithm called partition-based LEACH (pLEACH), which firstly partitions the network into optimal number of sectors, and then selects the node with the highest energy as the head for each sector, using the centralized calculations. The simulation results and analysis show that pLEACH could achieve much better performance of WSN in terms of the energy dissipation, network lifetime and quality of communication.

Wireless Sensor Networks (WSNs) is the vast area and developing very speedily now-a-days. This paper gives some of the major applications and critical limitations of WSNs like power and lifespan, communication bandwidth, memory size. Sensor nodes are working by node energy so the energy consumption is the essential issue in WSN. Routing in WSN consumes more energy than any other phase. Various routing techniques in WSNs are discussed and different routing protocols are illustrated. Low Energy Adaptive Clustering Hierarchy (LEACH) is one of the popular and feasible hierarchical clustering routing protocols in WSN. Working of LEACH is explained in brief. Furthermore, the descendants of LEACH e.g. LEACH-C (Centralized LEACH), LEACH-B (Balanced LEACH), LEACH-F, Multihop LEACH, MS-LEACH (Multihop and Single hop LEACH), MH-LEACH etc. are discussed in terms of the energy utilization. By analyzing the variants of LEACH, it is observed that the energy requirement in the cluster set up phase or data transmission phase is minimized to minimize the total energy consumption of the WSN. To elect the proper cluster head node, centralized approach is followed. Afterwards, data transmission will use the multihop communication technique. This will help to save some energy when base station is located far away from the cluster head node. Proposed protocol aims to decrease the energy overhead of the sensor nodes. The new approach is proposed entitled PV-LEACH which will save the energy consumption in cluster setup phase and also in data transmission phase of the conventional LEACH protocol. So, this will enhance the performance ratio in terms of energy consumption and life time of the sensor nodes.

Wireless sensor networks (WSN) consist of large number of sensor nodes. These small and low cost sensor nodes are deployed in monitoring region of interest. Since sensors perform multiple functions such as data gathering and data transmission results in energy depletion, these effects the network lifetime. The nodes having tendency to fail due to energy depletion is the critical issue in WSN. Due to wide number of applications of WSN, it is required to enhance the life time of entire network. Proposed method in this paper is aimed to optimize the energy dissipation by modifying the CH (Cluster Head) selection approach in LEACH (Low Energy Adaptive Clustering Hierarchy) algorithm and avoids the energy-hole problem considering mobility to the sink node which helps to prolong the lifetime of entire network.

Wireless sensor network (WSN), a network of minute interconnected sensing element nodes communicating within themselves utilizing radio frequency signals and utilized in immensely enormous quantities to examine and realize the physical world. The communicating sensing element nodes are power-driven by batteries, which have a circumscribed lifetime. Hence managing the energy is a primary requisite for the design of WSN. In this paper, an efficient wireless sensor network utilizing a cooperative Multiple Input Multiple Output (MIMO) predicated on Space Time Trellis Code (STTC) is proposed. This STTC based cooperative MIMO technique is incorporated into Exclusive OR — Low Energy Adaptive Clustering Hierarchy (XOR-LEACH) protocol. For selection of cluster head, the last cluster head and a arbitrary binary vector are XORed together. The proposed system obtains amended performance and is compared with the existing LEACH protocol in terms of network lifespan and residual energy. This system performance in terms of Bit Error Rate (BER) has been analyzed for various detection techniques.

One of the main emphases of the prevalent clustering and routing algorithms in wireless sensor networks is efficient energy utilization aimed towards enhanced network lifetime. In this paper we are proposing a clustering approach where the sensor nodes are clustered together based on a defined spatial correlation and the geographical location of each sensor nodes. The Cluster Head or Cluster Leader along with routing path is decided by our proposed algorithm based on the estimated chance-value during each rounds of data transfer. Thus in our scheme a multi-hop routing is effected wherein either two-level or three-level hops are dynamically chosen based on the spatial correlation existing between the nodes for the data transfer from the sensing node to the sink. It has been observed that our proposed algorithm outperforms the standard algorithms namely Low Energy Adaptive Clustering Hierarchy (LEACH), Stable Election Protocol (SEP) and Distributed Energy Efficient Clustering (DEEC) Protocol with regards to system throughput and Network Lifespan of WSN.

Energy efficient routing is the paramount point of significance in any wireless sensor network (WSN) so that the network sustains without any human intervention. Various energy efficient protocols have been proposed, multi-level Low Energy Adaptive Clustering Hierarchy (LEACH) being one among these. The multi-level LEACH protocol involves election of cluster heads at various hierarchical levels. If the area of deployment is large, the farther cluster heads cannot reach the base station directly. In such cases, it is needed to make use of an energy efficient routing technique for communication among cluster heads and forward the data towards the base station. Energy consumption is reduced by adopting routing mechanisms based on multi-hop and inverted tree in this multi-level LEACH protocol. This work deals with multi-level LEACH comprising of 1L-LEACH and 2L-LEACH. Directed diffusion carried out in 1L-LEACH and flat topology are compared with flooding. In directed diffusion, routing is done between a source and a sink optimizing the path taken. NS-3 simulation platform has been used and the results are presented.

Wireless Sensor Networks (WSNs) allow a large area to be monitored with various sensors. WSNs, although useful, are subject to Black Hole attacks. Defenses against attacks typically require more energy which reduces WSN lifetime. This thesis proposes a novel approach to detect and recover from attacks using an improved version of Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. LEACH is an energy efficient protocol for groups of battery-operated computers with sensor components in WSNs. This protocol works by having a node become a cluster head responsible for sending data to a sink. The sink can be either an access point or base station. After a set time the cluster heads go back to being regular nodes and a completely new set of nodes become cluster heads. There are secure versions of LEACH such as S-LEACH and MS-LEACH that provide encryption, but LEACH and its encrypted variants do not secure against Black Hole attacks. Our proposed approach, referred to as Anomaly Report Cycling - Low Energy Adaptive Clustering Hierarchy (ARC-LEACH), aims to provide defense from Black Hole attacks while also providing low energy cost. ARC-LEACH does this by absorbing an attack. When an attack occurs, it rotates cluster heads to reestablish communication, then sending a message from the sink to coordinate all nodes against the malicious nodes. ARC-LEACH actively blocks malicious nodes while leveraging the resilience of LEACH by building up stronger resistance to attacks. ARC-LEACH provides more defense capability when under attack from multiple malicious nodes that would otherwise be defenseless by LEACH, with only a limited increase in power consumption. The prototype for ARC-LEACH is implemented to show feasibility of the proposed approach.

Wireless Sensor Networks (WSN) is an ever growing field owing to their extensive variety of applications. WSN have limited battery energy, consequently, an energy efficient routing protocol is of major concern. LEACH (Low Energy Adaptive Clustering Hierarchy) is one of the fundamental clustering protocols in WSN that provides high energy efficiency. Many protocols have been derived from LEACH which mostly address a single inherent challenge. Instead of focusing on a single parameter, combining independent techniques can compound gains in energy efficiency. This paper proposes Yet Another LEACH (YA-LEACH) which uses centralised cluster formation to ensure optimal clusters and allow Cluster Heads (CH) to extend operation into multiple rounds to achieve energy savings. Also, the proposed protocol will have an alternative (vice) CH that takes over when CH residual energy reaches a critically low level. The extended protocol was simulated on NS2 with results showing an improvement in network lifetime and overall data throughput.

Wireless Sensor Network (WSN) is a self-configured network of light-weight nodes, that are used in many applications by sending their data through this network to a Base Station (BS), which in turn, delivers the data to its final destination. In WSN, the sensor node’s energy is usually limited, and thus, the overall power consumption of the network is a real challenge. Numerous methods have been proposed to overcome this challenge by improving the overall power consumption and thus, prolonging the lifetime of the network. Low Energy Adaptive Clustering Hierarchy (LEACH) protocol has been considered as a leading routing protocol in WSN, due to its low power consumption resultant from its cluster-based behavior. However, for dense networks, LEACH suffers from large burden over cluster head (CH), which might result in packet loss due to the induced congestion in the CH. In this paper, an improved algorithm based on LEACH is proposed to maximize the lifetime of WSN, by using another node to relieve CH’s burden. The routing path selection process is refined through selecting a new node that has the highest residual energy in each cluster to be an alternative gateway for the cluster head. Then, the routing path will be decided based on distance. This modified algorithm outperforms the original LEACH by 4.35% increase in the residual energy, which prolongs the network lifetime. However, there is a slight increase in the overhead ratio.

An on-demand weighed clustering algorithm is proposed against the limitation of wireless sensor network nodes with limited energy. This algorithm obtains more local network information by means of information interaction between nodes, and by comprehensively considering such factors as the current energy value, degree and transmission power, etc. of nodes, it makes different clustering decisions as per different application backgrounds of networks. Simulation results show that this algorithm has a more rational clustering by reducing energy consumption and lengthening network lifetime, compared to Low Energy Adaptive Clustering Hierarchy, a representative clustering algorithm.

For a network, two key evaluation indicators are the network lifetime and network throughput. Different clustering algorithms can be promoted for different aspects. A reasonable clustering algorithm can effectively improve the load balancing of the network and can make the distribution of CHs (cluster heads) more uniform. Aiming at the problem of cluster preference, this article presents an improved algorithm based on the classical LEACH (Low Energy Adaptive Clustering Hierarchy) algorithm, which takes the residual Energy of nodes and the uniformity of node distribution as the primary consideration for selecting CH.

Wireless sensor networks (WSNs) consist of a large number of small, low data rate and inexpensive nodes that communicate in order to sense or control a physical phenomenon. The major difference between the WSN and the traditional wireless network is that sensors are very sensitive to energy consumption. Moreover, the performance of the sensor network applications highly depends on the lifetime of the network and we expect the lifetime of several months to several years. Thus, energy saving is crucial in designing long-lived wireless sensor networks. Many researchers have focused on developing energy efficient cluster based protocols for WSNs, but there has not been much research on event driven WSNs and, their focus is on continuous driven networks. In this paper, we propose a modified algorithm of Low Energy Adaptive Clustering Hierarchy (LEACH) protocol which is a well known energy efficient clustering algorithm for WSNs. Our modified protocol called “Adaptive and Energy Efficient Clustering Algorithm for Event-Driven Application in Wireless Sensor Networks (AEEC)” is aimed at prolonging the lifetime of a sensor network by balancing energy usage of the nodes. AEEC makes the nodes with more residual energy have more chances to be selected as cluster head. Also, we use elector nodes which take the responsibility of collecting energy information of the nearest sensor nodes and selecting the cluster head. We compared the performance of our AEEC algorithm with the LEACH protocol using simulations .